1. Field of the Invention
This invention relates generally to an industrial process and, more particularly, to a method and apparatus for determining process targets using a probability constrained optimization with a receding horizon.
2. Description of the Related Art
There is a constant drive within the semiconductor industry to increase the quality, reliability and throughput of integrated circuit devices, e.g., microprocessors, memory devices, and the like. This drive is fueled by consumer demands for higher quality computers and electronic devices that operate more reliably. These demands have resulted in a continual improvement in the manufacture of semiconductor devices, e.g., transistors, as well as in the manufacture of integrated circuit devices incorporating such transistors. Additionally, reducing the defects in the manufacture of the components of a typical transistor also lowers the overall cost per transistor as well as the cost of integrated circuit devices incorporating such transistors.
Generally, a set of processing steps is performed on a wafer using a variety of processing tools, including photolithography steppers, etch tools, deposition tools, polishing tools, rapid thermal processing tools, implantation tools, etc. One technique for improving the operation of a semiconductor processing line includes using a factory wide control system to automatically control the operation of the various processing tools. The manufacturing tools communicate with a manufacturing framework or a network of processing modules. Each manufacturing tool is generally connected to an equipment interface. The equipment interface is connected to a machine interface which facilitates communications between the manufacturing tool and the manufacturing framework. The machine interface can generally be part of an advanced process control (APC) system. The APC system initiates a control script based upon a manufacturing model, which can be a software program that automatically retrieves the data needed to execute a manufacturing process. Often, semiconductor devices are staged through multiple manufacturing tools for multiple processes, generating data relating to the quality of the processed semiconductor devices. Pre-processing and/or post-processing metrology data is supplied to process controllers for the tools. Operating recipe parameters are calculated by the process controllers based on the performance model and the metrology information to attempt to achieve post-processing results as close to a process target value as possible. Reducing variation in this manner leads to increased throughput, reduced cost, higher device performance, etc., all of which equate to increased profitability.
Process control is becoming increasingly important in the semiconductor industry as production specifications are becoming less tolerant to variance in product quality. Historically, semiconductor process control has consisted of independent unit operation run-to-run controllers where the process targets are determined by individual operation models and do not consider the process as a whole. Run-to-run controllers have been employed to control these independent unit operations, such as chemical mechanical planarization, chemical vapor deposition, rapid thermal annealing, plasma etching, etc., and the run-to-run control algorithms, which are designed to maintain the unit operations at the desired process targets, are well understood. A run-to-run controller typically focuses on only one process and its associated process target value. Each run-to-run controller attempts to achieve its process target value within an acceptable range of variation. The process target value is typically set near the middle of a range of acceptable values for the characteristic controlled. However, there are typically numerous process steps that affect the outcome of a particular performance characteristic of the completed device. Because each individual process has its own process target value and controller attempting to reach that process target value, it is difficult to control the performance characteristic.
In some cases, electrical measurements that determine the performance of the fabricated devices are not conducted until relatively late in the fabrication process, and sometimes not until the final test stage. This lag between the fabrication of the devices and the measurement of their performance characteristics makes it difficult to automatically control the fabrication processes to achieve the performance goals.
Typically, the performance characteristics (e.g., speed, contact resistance, power consumption, etc.) of the devices manufactured are indirectly controlled by controlling the physical characteristics of the devices based on the design values determined for the dimensions and materials for the features. Variations in the actual device characteristics from the process target values cause corresponding variation in the performance characteristics. In some cases, a plurality of sources of variation may combine in an additive fashion to cause the electrical performance characteristics of the completed devices to be degraded or entirely unacceptable.
Typically, there may be more than one set of design or process target values that can be used to achieve a particular performance characteristic goal. However, because an indirect method of controlling the electrical performance characteristics is employed, the process target values are typically static. In some situations, one or more of the fabrication processes may have difficulty reliably meeting its process target. Various factors, such as tool cleanliness, age of consumable items, etc., can affect the performance and controllability of a tool. This variation from target deleteriously affects the electrical performance characteristics of the completed devices in a manner that is not readily accounted for by indirect control.
The present invention is directed to overcoming, or at least reducing the effects of, one or more of the problems set forth above.